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Record W1968416256 · doi:10.4236/psych.2014.510132

Cosmetic Surgery as Intrasexual Competition: The Mediating Role of Social Comparison

2014· article· en· W1968416256 on OpenAlexaff
Steven Arnocky, Tina Piché

Bibliographic record

VenuePsychology · 2014
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsNipissing University
Fundersnot available
KeywordsPsychologyCompetition (biology)Ecology

Abstract

fetched live from OpenAlex

Cosmetic surgical procedures have previously been associated with some risks to psychological and physical health. Yet such procedures are on the rise, highlighting the need for a better understanding of the factors which might underlie the decision to undergo cosmetic surgery. In a sample of 297 young adults (192 women), we examined the relationship between intrasexual competition (IC), social comparison, and individuals’ attitudes, perceived risks, and desired spending on cosmetic surgical procedures. Results showed that women perceived more risk to cosmetic surgery, yet held more positive attitudes and desire to spend on cosmetic surgery compared to men. For both men and women, IC predicted positive attitudes and desired spending on cosmetic surgery. Social comparison mediated all relationships between IC and cosmetic surgery variables. Cosmetic surgery is discussed as a potential form of intrasexual competition rooted in the mate-preferences of the opposite sex.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.383
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations104
Published2014
Admission routes1
Has abstractyes

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